Improved constitutive model suitable for line hardware wear simulation and undetermined parameter fitting method thereof

Abstract

The invention provides an improved constitutive model suitable for line hardware wear simulation and an undetermined parameter fitting method of the improved constitutive model. The Johnson-Cook constitutive model improves the influence of a plastic deformation item and a strain rate item on flow stress. According to the method, by improving the strain rate related items of a traditional Johnson-Cook constitutive model, the stress-strain relation under impact loads such as instantaneous strong wind can be better described, and therefore the improved Johnson-Cook constitutive model has higher precision when the abrasion behavior of the transmission line hardware fitting is simulated.

Description

Technical Field

[0001] The present invention belongs to the field of power transmission and transformation equipment operation and maintenance, and in particular relates to an improved constitutive model suitable for line hardware wear simulation and a method for fitting undetermined parameters thereof. Background Art

[0002] Wear of transmission line hardware is a key factor affecting the safe operation of transmission lines. Currently, the wear process and influencing factors of transmission line hardware are primarily studied using abrasive wear tests conducted using a wear swing tester. This method is not only labor-intensive and resource-intensive, but also limited in the test conditions it can simulate. Many extreme weather conditions cannot be simulated using a wear swing tester. Using finite element software to simulate the wear process is gaining increasing attention as a useful supplement to the study of transmission line hardware wear mechanisms.

[0003] When performing finite element simulations of the wear process, the constitutive relationship and fracture criteria of the hardware material must be input. In finite element software, the existing constitutive relationship is the traditional Johnson-Cook relationship. This traditional Johnson-Cook relationship cannot accurately describe the wear behavior of transmission line hardware in transient high winds. Summary of the Invention

[0004] In view of this, the present invention aims to overcome the shortcomings of the existing technology by proposing an improved constitutive model suitable for line hardware wear simulation and a method for fitting its undetermined parameters. This invention provides a data fitting method for the six undetermined parameters of the improved Johnson-Cook constitutive model. This improved Johnson-Cook constitutive model can better describe the stress-strain relationship of transmission line hardware under impact loads such as instantaneous high winds.

[0005] To achieve the above object, the technical solution of the present invention is achieved as follows:

[0006] In the first aspect, the present invention proposes an improved Johnson-Cook constitutive model for hardware wear simulation. The improved Johnson-Cook constitutive model is:

[0007]

[0008] Among them, σ eq is the equivalent stress, ε eq is the equivalent strain, ε eq * =ε eq / ε0 is the dimensionless equivalent plastic strain rate, ε0 is the reference strain rate, T * =(TT r ) / (T m -T r) is the dimensionless temperature, T is the current test temperature, T r is the reference temperature of the hardware material, T m is the melting point temperature of the hardware material, A, B1, B2, C, k, and m are material parameters, among which A, B1, and B2 are plastic deformation parameters, and C, k, and m are strain rate parameters.

[0009] Furthermore, the plastic deformation parameters A, B1, and B2 in the improved Johnson-Cook constitutive model are obtained by fitting the tensile test data at a reference strain rate and a reference temperature using the linear least squares method.

[0010] Furthermore, the strain rate term parameters C and k in the improved Johnson-Cook constitutive model are obtained by using a nonlinear least squares fitting method based on tensile test data at reference temperature and different strain rates.

[0011] Furthermore, the objective function in the nonlinear least squares fitting method is the square of the error 2-norm, which is calculated by calculating the Jacobian matrix of the objective function with respect to the strain rate term parameters C and k and solving the incremental equation.

[0012] Furthermore, the strain rate parameter m in the improved Johnson-Cook constitutive model is obtained by first performing logarithmic transformation on the reference strain rate and tensile test data at different temperatures and then using a linear least squares fitting method.

[0013] Furthermore, the calculation method of the plastic deformation parameters A, B1, and B2 in the improved Johnson-Cook constitutive model is:

[0014] The tensile test of the specimen was carried out at the reference strain rate and reference temperature, and the measured data were (ε eqi ,σ eqi ), i=1,2…n, n is the number of tensile test data points, then the calculation formulas of A, B1, and B2 are:

[0015]

[0016] in:

[0017]

[0018]

[0019] Furthermore, the calculation method of the strain rate term parameters C and k in the improved Johnson-Cook constitutive model is:

[0020] At reference temperature and different strain rates ε eqj *The tensile test of the sample was carried out under the condition of eqji ,σ eqji ), j = 1, 2, ... N, N is the number of tests at different strain rates, i = 1, 2 ... M, M is the number of tensile test data points at each strain rate, let:

[0021]

[0022] At different strain rates ε eqj * Next ji The average value is:

[0023]

[0024] Reconstruct the data points (ε eqj * , ), and the parameters C and k are calculated by the nonlinear least squares fitting method.

[0025] Furthermore, the calculation method of the nonlinear least squares fitting method is:

[0026] (a) Construct the objective function:

[0027]

[0028] (b) Set the number of iterations n1 = 1, the initial value [C; k] = [0.01; 0.5], the step size h = 1e-4, the iteration error e = 1e-6, and the maximum number of iterations 1e6;

[0029] (c) For the n1th iteration, calculate the Jacobian matrix:

[0030]

[0031] (d) Solve the incremental equation:

[0032]

[0033] Among them, ΔC and Δk are the increments of strain rate parameter C and strain rate parameter k respectively, e 2 (C,k) is the objective function;

[0034] (e) If ΔC and Δk are both smaller than the iteration error e, the calculation is terminated; if ΔC and Δk are larger than the iteration error e, let [C(n1); k(n1)] = [C(n1-1); k(n1-1)] + [ΔC(n1); Δk(n1)], n1 = n1+1, when n1 is smaller than the maximum number of iterations, return to step (c); when n1 is equal to the maximum number of iterations, the program is terminated, and the initial value of [C; k] is replaced and the calculation is restarted.

[0035] Furthermore, the method for determining the strain rate parameter m in the improved Johnson-Cook constitutive model is as follows:

[0036] At the reference strain rate and different temperatures T p * The tensile test of the sample was carried out under the condition of eqpi ,σ eqpi ), p=1,2,…P, P is the number of tests at different temperatures, i=1,2…M, M is the number of tensile test data points at each temperature, let:

[0037]

[0038] At different reference temperatures T p * Next pi The average value is:

[0039]

[0040] Reconstructed data points (T p * , ) is converted into logarithmic coordinate system data:

[0041]

[0042] The strain rate parameter m is calculated by least squares fitting:

[0043]

[0044] In a second aspect, the present invention proposes an electronic device comprising a processor and a memory connected to the processor for storing instructions executable by the processor, wherein the processor is used to execute the above-mentioned improved Johnson-Cook constitutive model for hardware wear simulation.

[0045] In a third aspect, the present invention proposes a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the above-mentioned improved Johnson-Cook constitutive model for hardware wear simulation.

[0046] Compared with the prior art, the present invention has the following advantages:

[0047] (1) The improved Johnson-Cook constitutive model proposed in this invention can better describe the stress-strain relationship under impact loads such as instantaneous strong winds by improving the strain rate-related terms of the traditional Johnson-Cook constitutive model. Therefore, the improved Johnson-Cook constitutive model has higher accuracy in simulating the wear behavior of transmission line hardware.

[0048] (2) For the six undetermined model parameters A, B1, B2, C, k, and m in the improved Johnson-Cook constitutive model, A, B1, and B2 can be obtained by linear least squares fitting based on the tensile test measurement data at the reference strain rate and reference temperature. C and k can be obtained by nonlinear least squares fitting based on the tensile test measurement data at the reference temperature and different strain rates. m can be obtained by first performing logarithmic transformation and then linear least squares fitting based on the tensile test measurement data at the reference strain rate and different temperatures. Once the six model parameters are determined, the improved Johnson-Cook constitutive model can be embedded in the finite element software material library, thereby achieving more accurate simulation of the hardware wear process. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The accompanying drawings, which constitute part of the present invention, are provided to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are provided to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0050] Figure 1 Schematic diagram of the stretching machine;

[0051] Figure 2 is the stress-strain curve at reference temperature and different strain rates;

[0052] Figure 3 is the stress-strain curve at the reference strain rate and different temperatures;

[0053] Figure 4 The stress-strain relationship of the tensile test measurement data, the traditional Johnson-Cook constitutive model and the improved Johnson-Cook constitutive model at the reference strain rate and reference temperature;

[0054] Figure 5 The stress-strain relationship of the tensile test measurement data, the traditional Johnson-Cook constitutive model and the improved Johnson-Cook constitutive model at reference temperature and different strain rates;

[0055] Figure 6 The stress-strain relationship of tensile test measurement data at reference strain rate and different temperatures, traditional Johnson-Cook constitutive model and improved Johnson-Cook constitutive model. DETAILED DESCRIPTION

[0056] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0057] The following describes in detail embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0058] The present invention proposes an improved constitutive model suitable for line hardware wear simulation and a method for fitting its undetermined parameters. The improved Johnson-Cook constitutive model is embedded in the finite element software material library to realize the simulation of the hardware wear process. The improved Johnson-Cook constitutive model improves the influence of plastic deformation terms (A, B1, B2) and strain rate terms (C, k, m) on rheological stress.

[0059] Among them, the method for determining the plastic deformation parameters (A, B1, B2) includes:

[0060] Step S1: Prepare a tensile test specimen of a hardware material according to GB / T 228.1-2021 standard, and perform a tensile test on the specimen at a reference strain rate and reference temperature;

[0061] Step S2: performing data fitting on the tensile test data at the reference strain rate and reference temperature; step S2 is calculated by the least squares method;

[0062] The methods for determining the strain rate parameters (C, k) include:

[0063] Step S3: performing a tensile test on the sample at a reference temperature and different strain rates;

[0064] Step S4: fitting the tensile test data at the reference temperature and different strain rates; in step S4, the nonlinear least squares method is used for calculation; in step S4, the objective function is the square of the 2-norm of the error; the parameters C and k are optimized by calculating the Jacobian matrix of the objective function for the parameters C and k and solving the incremental equation;

[0065] The method for determining the strain rate parameter m includes:

[0066] Step S5: performing a tensile test on the specimen at a reference strain rate and different temperatures;

[0067] Step S6: performing data fitting on the reference strain rate and different temperature tensile test data;

[0068] In step S6, the tensile test data is calculated in logarithmic coordinates;

[0069] In step S6, a linear least squares calculation is performed on the logarithm of the tensile test data.

[0070] The specific calculation process is as follows:

[0071] When finite element software is used to simulate the wear process, the material model library uses the traditional Johnson-Cook constitutive model, which is expressed as follows:

[0072]

[0073] where σ eq is the equivalent stress, ε eq is the equivalent strain, ε eq * =ε eq / ε0 is the dimensionless equivalent plastic strain rate, ε0 is the reference strain rate, T * =(TT r ) / (T m -T r ) is the dimensionless temperature, T is the current test temperature, T r is the reference temperature of the hardware material, T m is the melting point temperature of the hardware material, and the five parameters A, B, C, n and m are the material parameters of the Johnson-Cook model.

[0074] The traditional Johnson-Cook constitutive relationship cannot accurately describe the stress-strain relationship of hardware materials under impact loads such as instantaneous strong winds, resulting in a large error between the finite element simulation results and the experimental results of transmission line hardware wear. This paper proposes an improved Johnson-Cook constitutive model:

[0075]

[0076] Among them, the six parameters A, B1, B2, C, k and m are the unknown parameters of the Johnson-Cook constitutive model.

[0077] The data fitting method for the undetermined parameters A, B1, B2, C, k and m is:

[0078] (1) Prepare the tensile test specimens of the hardware materials in accordance with GB / T 228.1-2021 and perform the tensile test on the specimens at the reference strain rate and reference temperature;

[0079] (2) At the reference strain rate and reference temperature, the improved Johnson-Cook constitutive model (2) can be rewritten as:

[0080]

[0081] The measured data of the tensile test of the specimen at the reference strain rate and reference temperature is (ε eqi ,σ eqi ), i = 1, 2…n, where n is the number of tensile test data points, then A, B1, and B2 can be calculated using the least squares method:

[0082]

[0083] in:

[0084]

[0085] (3) At the reference temperature and different strain rates, the improved Johnson-Cook constitutive model (2) can be rewritten as:

[0086]

[0087] Different strain rates ε eqj * (j=1,2,…N, N is the number of tests at different strain rates) Specimen tensile test (ε eqji ,σ eqji ), i=1,2…M, M is the number of tensile test data points at each strain rate, let:

[0088]

[0089] Then at the strain rate ε eqj * Next ji The average value is:

[0090]

[0091] Reconstruct the data points (ε eqj * , ), C and k are calculated by the nonlinear least squares fitting method, and the calculation process is as follows:

[0092] (a) Construct the objective function:

[0093]

[0094] (b) Set the number of iterations n1 = 1, the initial value [C; k] = [0.01; 0.5], the step size h = 1e-4, the iteration error e = 1e-6, and the maximum number of iterations 1e6;

[0095] (c) For the n1th iteration, calculate the Jacobian matrix:

[0096]

[0097] (d) Solve the incremental equation:

[0098]

[0099] Where ΔC and Δk are the increments of parameters C and k respectively, e 2 (C,k) is formula (17).

[0100] (e) If both ΔC and Δk are less than the iteration error e, the calculation terminates. If both ΔC and Δk are greater than the iteration error e, set [C(n1);k(n1)]=[C(n1-1);k(n1-1)]+[ΔC(n1);Δk(n1)], with n1=n1+1. If n1 is less than the maximum number of iterations, return to step (c). If n1 is equal to the maximum number of iterations, the program terminates and the calculation restarts with a new initial value for [C;k].

[0101] (4) At the reference strain rate and different temperatures, the improved Johnson-Cook constitutive model (2) can be rewritten as:

[0102]

[0103] Different temperatures T p * (p=1,2,…P, P is the number of tests at different temperatures) Specimen tensile test (ε eqpi ,σ eqpi ), i=1,2…M, M is the number of tensile test data points at each temperature, let:

[0104]

[0105] Then at temperature T p * Next pi The average value is:

[0106]

[0107] Reconstructed data points (T p * , ) is converted into logarithmic coordinate system data:

[0108]

[0109] The parameter m can be calculated by least squares fitting

[0110]

[0111] The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0112] Example 1

[0113] (1) Adoption Figure 1 The tensile testing machine was used to conduct tensile tests on 35# steel for transmission line fittings. The indoor temperature was 20℃, the initial gauge length was 50mm, and the reference strain rate was 8.33×10 -4 s -1 (corresponding to a stretching speed of 2 mm / min).

[0114] The stress-strain curves at reference temperature and different strain rates are as follows: Figure 2 As shown, the stress-strain curves at the reference strain rate and different temperatures are as follows Figure 3 shown.

[0115] (2) Yes Figure 2 The medium tensile speed is 2 mm / min, which means the reference strain rate is 8.33×10 -4 s -1 The data were fitted and the parameters A, B and n of the traditional Johnson-Cook constitutive model were obtained as follows: A = 27.4, B = 410.8, n = 0.1578. The parameters A, B1 and B2 of the improved Johnson-Cook constitutive model were calculated by formulas (4)-(6) as follows: A = 241.8, B1 = 807.9, B2 = -1281.5. The stress-strain relationship of the tensile test measurement data, the traditional Johnson-Cook constitutive model and the improved Johnson-Cook constitutive model at the reference strain rate and reference temperature is shown in Figure 2. Figure 4 As shown in Figure 3, it can be seen that the improved Johnson-Cook constitutive model fits the tensile test measurement data at the reference strain rate and reference temperature better than the traditional Johnson-Cook constitutive model.

[0116] (3) Conduct tensile tests at reference temperature and different strain rates, and process the data. The strain rate is 8.33×10 -4 s -1 (tensile speed 2mm / min), 4.17×10 -3 s -1 (tensile speed 10 mm / min), 4.17×10 -2 s -1 (tensile speed 100 mm / min), 8.33×10 -2 s -1 (tensile speed 200mm / min), 0.1251s -1 (tensile speed 300mm / min), 0.1668s -1 (tensile speed 400mm / min), 0.2085s -1(tensile speed 500mm / min), 0.2052s -1 (tensile speed 600mm / min), 0.2919s -1 (tensile speed 700 mm / min) and 0.3336 s -1 (tensile speed 800 mm / min), the improved Johnson-Cook constitutive model parameters C and k are obtained by nonlinear least square method according to formula (15) and formula (16): C = 7.05 × 10 -4 , k = 0.614, and the value of the traditional Johnson-Cook constitutive model parameter C is obtained by the least squares method: C = 7.05×10 -4 The tensile test data at different strain rates, the stress-strain relationship of the traditional Johnson-Cook constitutive model and the improved Johnson-Cook constitutive model are shown in Figure 2. Figure 5 As shown, from Figure 5 It can be seen that the improved Johnson-Cook constitutive model fits the tensile test data at reference temperature and different strain rates better than the traditional Johnson-Cook constitutive model.

[0117] (4) Conduct tensile tests at reference strain rates and different temperatures, and process the data. The strain rate is 8.33×10 -4 s -1 (tensile speed 2mm / min), the test curves at different temperatures are as follows Figure 3 As shown in Figure 2, the improved Johnson-Cook constitutive model parameter m is calculated using equations (22)-(24) for the tensile test data at different temperatures, and the value of the traditional Johnson-Cook constitutive model parameter m is 0.578, while the value of the traditional Johnson-Cook constitutive model parameter m is 0.515. The stress-strain relationship of the reference strain rate and tensile test measurement data at different temperatures, the traditional Johnson-Cook constitutive model, and the improved Johnson-Cook constitutive model is shown in Figure 2. Figure 6 As shown, from Figure 6 It can be seen that the improved Johnson-Cook constitutive model fits the reference strain rate and the tensile test measurement data at different temperatures better than the traditional Johnson-Cook constitutive model.

[0118] from Figure 4 、 Figure 5 and Figure 6 It can be seen that compared with the traditional Johnson-Cook constitutive model, the improved Johnson-Cook constitutive model has higher accuracy in describing the stress-strain relationship and wear behavior of transmission line hardware.

[0119] Example 2

[0120] An electronic device includes a processor and a memory communicatively connected to the processor and used to store instructions executable by the processor. The processor is used to execute the above-mentioned improved constitutive model suitable for circuit hardware wear simulation and the method for fitting its undetermined parameters.

[0121] Example 3

[0122] A computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the improved constitutive model suitable for circuit hardware wear simulation and the method for fitting undetermined parameters thereof are obtained.

[0123] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this disclosure are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0124] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal information and ensure that others with access to personal information comply with its privacy policy and procedures.

[0125] This disclosure contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0126] The acquisition, transmission, storage, use, and processing of data in the technical solution disclosed herein are in compliance with the relevant provisions of national laws and regulations.

[0127] It should be noted that in the embodiments of the present disclosure, certain software, components, models and other existing solutions in the industry may be mentioned. They should be regarded as exemplary and their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use the solution.

[0128] In the descriptions of the aforementioned embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0129] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one such feature. Throughout the present disclosure, "plurality" means at least two, such as two, three, etc., unless otherwise specifically defined.

[0130] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present disclosure includes additional implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present disclosure belong.

[0131] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing it in a suitable manner if necessary, and then storing it in a computer memory.

[0132] It should be understood that various parts of the present disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0133] Those skilled in the art will appreciate that all or part of the steps in the method for implementing the above-mentioned embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0134] In addition, the functional units in the various embodiments of the present disclosure may be integrated into a single processing module, each unit may exist physically separately, or two or more units may be integrated into a single module. The aforementioned integrated modules may be implemented in the form of hardware or in the form of software functional modules. If the integrated modules are implemented in the form of software functional modules and sold or used as independent products, they may also be stored in a computer-readable storage medium.

[0135] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure. A person of ordinary skill in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present disclosure.

Claims

1. An improved Johnson-Cook constitutive model for hardware wear simulation, characterized by: The improved Johnson-Cook constitutive model is: Among them, σ eq is the equivalent stress, ε eq is the equivalent strain, ε eq * =ε eq / ε0 is the dimensionless equivalent plastic strain rate, ε0 is the reference strain rate, T * =(TT r ) / (T m -T r ) is the dimensionless temperature, T is the current test temperature, T r is the reference temperature of the hardware material, T m is the melting point temperature of the hardware material, A, B1, B2, C, k, and m are material parameters, among which A, B1, and B2 are plastic deformation parameters, and C, k, and m are strain rate parameters.

2. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 1, characterized in that: The plastic deformation parameters A, B1, and B2 in the improved Johnson-Cook constitutive model are obtained by fitting the tensile test data at a reference strain rate and a reference temperature using the linear least squares method.

3. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 2, characterized in that: The strain rate term parameters C and k in the improved Johnson-Cook constitutive model are obtained by using a nonlinear least squares fitting method based on tensile test data at reference temperature and different strain rates.

4. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 3, characterized in that: The objective function in the nonlinear least squares fitting method is the square of the error 2-norm, which is calculated by calculating the Jacobian matrix of the objective function with respect to the strain rate term parameters C and k and solving the incremental equation.

5. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 1, characterized in that: The strain rate parameter m in the improved Johnson-Cook constitutive model is obtained by first performing logarithmic transformation on the reference strain rate and tensile test data at different temperatures and then using a linear least squares fitting method.

6. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 2, characterized in that: The calculation method of the plastic deformation parameters A, B1, and B2 in the improved Johnson-Cook constitutive model is: The tensile test of the specimen was carried out at the reference strain rate and reference temperature, and the measured data were (ε eqi ,σ eqi ), i=1,2…n, n is the number of tensile test data points, then the calculation formulas of A, B1, and B2 are: in:

7. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 6, characterized in that: The calculation method of the strain rate parameters C and k in the improved Johnson-Cook constitutive model is: At reference temperature and different strain rates ε eqj * The tensile test of the sample was carried out under the condition of eqji ,σ eqji ), j = 1, 2, ... N, N is the number of tests at different strain rates, i = 1, 2 ... M, M is the number of tensile test data points at each strain rate, let: At different strain rates ε eqj * Next ji The average value is: Reconstructing data points The parameters C and k are calculated by nonlinear least squares fitting method.

8. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 7, characterized in that: The calculation method of the nonlinear least squares fitting method is: (a) Construct the objective function: (b) Set the number of iterations n1 = 1, the initial value [C; k] = [0.01; 0.5], the step size h = 1e-4, the iteration error e = 1e-6, and the maximum number of iterations 1e6; (c) For the n1th iteration, calculate the Jacobian matrix: (d) Solve the incremental equation: Among them, ΔC and Δk are the increments of strain rate parameter C and strain rate parameter k respectively, e 2 (C,k) is the objective function; (e) If ΔC and Δk are both smaller than the iteration error e, the calculation is terminated; if ΔC and Δk are larger than the iteration error e, let [C(n1); k(n1)] = [C(n1-1); k(n1-1)] + [ΔC(n1); Δk(n1)], n1 = n1+1, when n1 is smaller than the maximum number of iterations, return to step (c); when n1 is equal to the maximum number of iterations, the program is terminated, and the initial value of [C; k] is replaced and the calculation is restarted.

9. The improved Johnson-Cook constitutive model for hardware wear simulation according to claim 5, characterized in that: The method for determining the strain rate parameter m in the improved Johnson-Cook constitutive model is: At the reference strain rate and different temperatures T p * The tensile test of the sample was carried out under the condition of eqpi ,σ eqpi ), p=1,2,…P, P is the number of tests at different temperatures, i=1,2…M, M is the number of tensile test data points at each temperature, let: At different reference temperatures T p * Next pi The average value is: Reconstructed data points The data converted into logarithmic coordinate system is: The strain rate parameter m is calculated by least squares fitting:

10. An electronic device, characterized in that: The system comprises a processor and a memory which is in communication with the processor and is used to store instructions executable by the processor. The processor is used to execute the above-mentioned improved Johnson-Cook constitutive model for hardware wear simulation.

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